{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:3FEIIBIKQ4WAZLKSRBKB66AR2D","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"a2306a169a7fe4a15ba5f4139ef4c0e856fadf181b95fe5f69254fafaed936b6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-23T00:04:31Z","title_canon_sha256":"5bcfb535064f747975c93dad104a76f8df7949861a3c9d1a9e2fd9158ddd1468"},"schema_version":"1.0","source":{"id":"2606.24026","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.24026","created_at":"2026-06-24T01:14:38Z"},{"alias_kind":"arxiv_version","alias_value":"2606.24026v1","created_at":"2026-06-24T01:14:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.24026","created_at":"2026-06-24T01:14:38Z"},{"alias_kind":"pith_short_12","alias_value":"3FEIIBIKQ4WA","created_at":"2026-06-24T01:14:38Z"},{"alias_kind":"pith_short_16","alias_value":"3FEIIBIKQ4WAZLKS","created_at":"2026-06-24T01:14:38Z"},{"alias_kind":"pith_short_8","alias_value":"3FEIIBIK","created_at":"2026-06-24T01:14:38Z"}],"graph_snapshots":[{"event_id":"sha256:7660e9a95d7d8e1b87cebd75ccad0e1c21d2673e128c44938751b7bcedb7aac8","target":"graph","created_at":"2026-06-24T01:14:38Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2606.24026/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Mechanistic interpretability has made substantial progress in automatically localizing circuits, but explaining what localized components do remains labor-intensive and difficult to standardize. In this work, we study whether language model (LM) agents can assist with this explanation problem once a circuit has already been identified. We introduce AgenticInterpBench, a benchmark for circuit explanation built from 84 semi-synthetic transformer circuits with 163 component-level annotations. We propose HyVE (Hypothesize, Validate, Explain), an agentic explainer that analyzes each component throu","authors_text":"Ayan Antik Khan, Harsh Kohli, Huan Sun, Yuekun Yao, Ziyu Yao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-23T00:04:31Z","title":"Can Language Model Agents be Helpful Circuit Explainers in Mechanistic Interpretability?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.24026","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:8b66955ebba703b85042d749690f5f65f2e3ed66d6e82bb7a95b6ea52c1c505a","target":"record","created_at":"2026-06-24T01:14:38Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"a2306a169a7fe4a15ba5f4139ef4c0e856fadf181b95fe5f69254fafaed936b6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-23T00:04:31Z","title_canon_sha256":"5bcfb535064f747975c93dad104a76f8df7949861a3c9d1a9e2fd9158ddd1468"},"schema_version":"1.0","source":{"id":"2606.24026","kind":"arxiv","version":1}},"canonical_sha256":"d94884050a872c0cad5288541f7811d0e82228fffe15880a1902ac70d9ebcab7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d94884050a872c0cad5288541f7811d0e82228fffe15880a1902ac70d9ebcab7","first_computed_at":"2026-06-24T01:14:38.467629Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-24T01:14:38.467629Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ksf5EWexicm06edtBsMaXeKHGhByajh9Ogz/XygfGlntORzl3b1E0qlWG6uQFhChwiZXn2fS6G9fGd3qim89Dw==","signature_status":"signed_v1","signed_at":"2026-06-24T01:14:38.468056Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.24026","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8b66955ebba703b85042d749690f5f65f2e3ed66d6e82bb7a95b6ea52c1c505a","sha256:7660e9a95d7d8e1b87cebd75ccad0e1c21d2673e128c44938751b7bcedb7aac8"],"state_sha256":"6259d62bbeedd731487c212b1070d750dfa8bf2a83af9d2d721b9a0ddc3f4d9b"}